Disclosed is a centralized system and method for metering, tracking, and monetizing distributed digital energy assets. The system includes the creation and utilization of a secure digital energy-asset that acts as a key, authorizing specialized circuits to generate a specified amount of electrical energy. Digital information passed through the system includes data necessary to ascribe attribution (i.e., branding, trail of ownership, etc.) and permit monetization (i.e., kWhs, time, dollars, geography, etc.). Functionality and/or value that is ascribed to the digital energy asset can be enhanced by appending additional information and/or utility. The system also includes a means to normalize and evaluate a potentially infinite number of measurements commonly used in business models across multiple industries to a simplified listing of measurements required to track and monetize energy alone within the system.

A method includes generating a time-varying charge/discharge control signal for an electrical storage device, wherein generating the time-varying charge/discharge control signal comprises identifying a prioritization order of a stack of simultaneously operating control modes, the stack of simultaneously operating control modes including a staging mode and at least two additional control modes, each control mode of the stack comprising a plurality of control signal candidate values; identifying an intersection of one or more control signal candidate values from the plurality of control signal candidate values of each control mode of the stack according to the prioritization order; and determining, based on the prioritization order, at least one time-varying charge/discharge control signal for the electrical energy storage device from the intersection of control signal candidate values.

An example system includes an aggregator configured to receive a service collaboration request and iteratively determine, based on minimum and maximum power values for DERs under its management, an optimized operation schedule. The aggregator may also be configured to iteratively determine, based on the optimized operation schedule, an estimated flexibility range for devices under its management and output an indication thereof. The system may also include a power management unit (PMU) configured to iteratively receive the indication and determine, based on a network model that includes the estimated flexibility range, a reconfiguration plan and an overall optimized operation schedule for the network. The PMU may also be configured to iteratively cause reconfiguration of the network based on the plan. The PMU and aggregator may also be configured to iteratively, at a fast timescale, cause energy resources under their management to modify operation based on the overall optimized operation schedule.

A method for controlling an electrical installation at least one of an electrical energy source or an energy sink. The electrical installation is coupled to a power grid. The method includes a period of time having a start time and a duration being specified, an upward flexibility Fo, which includes a forecast maximum feed-in power increase or feed-out power decrease, and a downward flexibility Fu, which includes a forecast maximum feed-out power increase or feed-in power decrease, being set for the period of time, a selling threshold price Pv and a purchasing threshold price Pe being set for the period of time, and an electricity trading transaction being concluded for the period of time. The electricity trading transaction includes a base value, a base quantity, a base price, a date on which the electricity trading transaction is to be carried out.

A method predicts a grid state of an electrical power distribution grid, in which a central computer arrangement is used to receive measured values from measuring devices. A state estimation device is used to predict a future grid state, wherein the prediction of the future grid state is taken as a basis for ascertaining measures to guarantee stability of the power distribution grid. The prediction is made for multiple times within a predefined time window. A first prediction device is used to ascertain a prediction for a first portion of the multiple times on the basis of a voltage var control method, and in that a second prediction device is used to ascertain a prediction for a second portion of the multiple times on the basis of a neural network method.

The present disclosure provides systems and methods for an operation of an electric power plant comprising a renewable energy resource and an energy storage device. The method may comprise determining, at a first time, a forecast of predicted energy production by the electric power plant over a time period subsequent to the first time based on a forecast for the time period; detecting a current state of charge of the energy storage device; calculating a range of automatic generation controls the electric power plant is capable of satisfying for the time period based on the forecast of predicted energy production and the detected current state of charge of the energy storage device; and signaling, from the electric power plant to a central utility controlling a power grid, the range of automatic generation controls the electric power plant is capable of satisfying for the time period.

Various implementations power homes and businesses without needing to connect to electric utility company-provided power, i.e., they can operate off-grid. Generally the system includes solar panel racks (e.g., photovoltaic cells on sheets stabilized using ballasts, anchors, or mounting) that generate electrical power used to provide power to a building or that is stored on batteries. The system includes the solar panel racks and an enclosure to be installed at the premises and separate from the building. The enclosure includes the batteries and inverters that are electronically connected to the solar panel racks and batteries. The inverters are configured to convert direct current (DC) electricity from the solar power racks and batteries to alternating current (AC) electricity to provide power to the building via wires electrically connecting the inverters to the main panel of the building.

In an energy time-shifting process, an electrical grid is monitored. Based on monitoring the electrical grid, it is determined that one or more criteria are satisfied at a first time. In response to determining that the one or more criteria are satisfied at the first time, water is directed from an aquifer located at a first elevation to a reservoir located at a second elevation. The first elevation is lower than the second elevation. Subsequent to directing the water from the aquifer to the reservoir, water is directed from the reservoir to a turbine generator located at a third elevation. The third elevation is lower than the second elevation and higher than the first elevation. Electrical power is generated using the turbine generated based on the water flowing through the turbine generator. Water is directed from the turbine generator into the aquifer.

Responsive to indication that a predicted amount of solar or wind power from a power generating event will exceed a power storage capability of one or more power storage devices configured to receive the solar or wind power, controllers may command the one or more power storage devices to discharge energy to a power grid before the power generating event such that the power storage capability of the one or more power storage devices increases.

Purchasing, maintaining, and deriving revenue from mobile autonomous units is facilitated by providing a mobile autonomous unit marketplace in which equity shares in mobile autonomous units can be bought, sold and traded. Valuation of mobile autonomous units within the marketplace can be a function of a variety of factors such as the mobile autonomous unit’s primary geographic region, and the number, diversity, and time management of revenue streams available to the mobile autonomous units.